1) Write a classifier function to accept a country code and output a continent (Africa, Asia, Australia, Europe, North and South America. (Let's put South Pacific countries with Australia.) Antarctica has no human citizens so we can skip them. The Country Codes in the data are ISO standards and can be found online. Here is one source (https://www.nationsonline.org/oneworld/country_code_list.htm(Links to an external site.))

2. Using Boston Marathon data (bm_results2012.csv), sample 20 runners from Europe and Africa and perform a t-test on the two samples.

name	city	gender	age	official	country
Masazumi Soejima	Fukuoka City	M	41	83.45	JPN
Gebregziabher Gebremariam	Tigray	M	27	142.93	ETH
Ernst F. Van Dyk	Paarl	M	39	84.38	RSA
Kurt H. Fearnley	Hamilton	M	31	81.65	AUS
Kota Hokinoue	Iizuka	M	38	83.43	JPN
Levy Matebo	Trans Nzoia	M	22	133.1	KEN
Sharon Cherop	Marakwet	F	28	151.83	KEN
Wilson Chebet	Marakwet	M	26	134.93	KEN
Joshua R. Cassidy	Toronto	M	27	78.42	CAN
Krige Schabort	Cedartown	M	48	83.73	USA
Firehiwot Dado	Assela	F	28	154.93	ETH
Laban Korir	Uasin Gishu	M	26	135.48	KEN
Adam Bleakney	Champaign	M	36	92.42	USA
Rita Jeptoo	Eldoret	F	31	155.88	KEN
Saul Mendoza	Wimberley	M	45	105.35	USA
Wesley Korir	Kenya	M	29	132.67	KEN
Michel Filteau	St Jean Baptite	M	45	86.83	CAN
Bernard Kipyego	Eldoret	M	25	133.22	KEN
Aaron L. Pike	Champaign	M	25	92.75	USA

3. The null hypothesis would be there is no significant difference in the times of runners from Africa and Europe. Use a cell of your workbook to explain whether this hypothesis was supported and why.